Feature generation method by geometrical interpretation of fisher linear discriminant analysis (特集:システム制御のための画像応用技術)
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概要
- 論文の詳細を見る
This paper presents a new algorithm for feature generation, which is derived based on geometrical interpretation of the fisher linear discriminant analysis (FLDA). This algorithm (Simple-FLDA) is an approximation algorithm that calculates eigenvectors sequentially by an easy iterative calculation by expressing the maximization of variance between classes and minimization of variance in each class without the use of matrix calculation. We carry out computer simulations about recognition of wrist motion patterns by EMG measured from wrist and personal authentications that use face images to verify the effectiveness of this technique. The result was compared with the result of principal component analysis (Simple-PCA).
- 社団法人 電気学会の論文
著者
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OYAMA Tadahiro
Kobe City College of Technology
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Fukumi Minoru
Department Of Information Science And Intelligent Systems University Of Tokushima
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Karungaru Stephen
Department Of Information Science And Intelligent Systems University Of Tokushima
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Oyama Tadahiro
Department of Information & Science Intelligent Systems, The University of Tokushima
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Matsumura Yuji
Department of Information & Science Intelligent Systems, The University of Tokushima
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Mitsukura Yasue
Graduate School Of Bio-applications And Systems Engineering Tokyo University Of Agriculture And Tech
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Matsumura Yuji
Department Of Gastroenterology Juntendo University
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Matsumura Yuji
Department Of Chest Surgery Ohta-nishinouchi Hospital
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Oyama Tadahiro
Department of Information & Science Intelligent Systems, The University of Tokushima
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Matsumura Yuji
Department of Information & Science Intelligent Systems, The University of Tokushima
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Karungaru Stephen
Department of Information & Science Intelligent Systems, The University of Tokushima
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